Research and Application of Multimodal Data Fusion Technology for Oil and Gas Pipelines

With the advent of the era of big data and artificial intelligence, pipeline enterprises are accumulating increasingly rich data. However, currently in the oil and gas pipeline industry, traditional pipeline data processing technologies are mostly aimed at single modal data, which can no longer meet the data needs of big data technology and artificial intelligence technology. Further research on multimodal data fusion technology for pipeline business scenarios is needed. Firstly, this paper investigates the current status of pipeline data fusion technology at home and abroad, constructs a pipeline big data technology architecture, analyzes the sources and types of pipeline data, and systematically elaborates on pipeline multimodal data fusion technology, including data conversion and fusion, logical association fusion, spatial analysis and fusion, semantic feature fusion. Secondly, the paper proposes a pipeline data lake technology architecture, providing services for subsequent data storage and analysis. Finally, this paper proposes that in the future, it is necessary to meet the data needs of new generation artificial intelligence technologies such as large models, and further research and application of multimodal data fusion technology should be carried out.